Existing approaches to resource allocation in a virtualized computing environment are typically based on relatively static and/or coarse-grained decisions about the expected workload to be processed within the virtualized computing environment. A virtualized computing environment typically includes multiple physical computing systems that each includes a hypervisor, virtual machine monitor, or similar logic that is configured to manage the concurrent execution of multiple virtual machines (VMs). Each virtual machine may have a distinct guest operating system and corresponding applications.
When a virtual machine is created, it may be assigned or given access to some portion of the physical resources of its host physical computing system. Typically, the amount of physical resources (e.g., a central processing unit (CPU) or memory) is allocated based on a preset value, without regard to specific user profile or specific group needs. For example, many organizations simply utilize a “one size fits all” approach to resource allocation, and provide a uniform resource set for virtual machines allocated for different users or uses. Such uniform allocation, while simple and seemingly fair, does not consider the actual computing needs of those users, which may vary dramatically based on differing roles they may play in an organization. Such uniform allocation decisions may result in a collection of virtual machines that may not be closely matched to their actual computing requirements, in that some virtual machines do not have sufficient resources, while others are allocated excess resources based on under utilization of the resources by the user.